Putting R in DBER

Many of things that this group will do rely on advanced statistical techniques and capabilities of the statistical program called R. This is an open-source language (meaning it is completely free of charge) that allows users to conduct beginner and advanced statistical analyses and a multitude of other features. I firmly believe that coding in R makes for higher quality research, particularly in exploratory studies in DBER.

If you’re interested in learning more about R or want to get started learning, I would strongly recommend this free, online resource called R For Data Science. This book is well-written and walks through the basics of coding in R in a newer, easier to read syntax called the tidyverse. Please feel free to ask me questions about R in DBER – I learned this program getting free help from experts around me and am always eager to share my perspectives in this program.

Public Access to Code

One of the central tenets of R is that it is open-source, meaning access for all. Here, I will periodically release code chunks that I believe are relevant to DBER members. If you have any questions about these code snippets, please do not hesitate to ask.

Putting the R in CER: How the Statistical Program R Transforms Research Capabilities. This is a book chapter that references a number of coding examples. The code examples and data are available here.

Novel test-retest reliability: In conjunction with a JCE article that describes this statistic, you can download code (.R) for the zeta-range estimator here.

At the 2018 BCCE, I gave a talk about different cluster analysis techniques. You can find the slides (which contain R code) here.